Extracting fetal heart beats from maternal abdominal recordings: Selection of the optimal principal components

This study presents a systematic comparison of different approaches to the automated selection of the principal components (PC) which optimise the detection of maternal and fetal heart beats from non-invasive maternal abdominal recordings. A public database of 75 4-channel non-invasive maternal abdominal recordings was used for training the algorithm. Four methods were developed and assessed to determine the optimal PC: (1) power spectral distribution, (2) root mean square, (3) sample entropy, and (4) QRS template. The sensitivity of the performance of the algorithm to large-amplitude noise removal (by wavelet de-noising) and maternal beat cancellation methods were also assessed. The accuracy of maternal and fetal beat detection was assessed against reference annotations and quantified using the detection accuracy score F1 [2*PPV*Se / (PPV + Se)], sensitivity (Se), and positive predictive value (PPV). The best performing implementation was assessed on a test dataset of 100 recordings and the agreement between the computed and the reference fetal heart rate (fHR) and fetal RR (fRR) time series quantified. The best performance for detecting maternal beats (F1 99.3%, Se 99.0%, PPV 99.7%) was obtained when using the QRS template method to select the optimal maternal PC and applying wavelet de-noising. The best performance for detecting fetal beats (F1 89.8%, Se 89.3%, PPV 90.5%) was obtained when the optimal fetal PC was selected using the sample entropy method and utilising a fixed-length time window for the cancellation of the maternal beats. The performance on the test dataset was 142.7 beats2/min2 for fHR and 19.9 ms for fRR, ranking respectively 14 and 17 (out of 29) when compared to the other algorithms presented at the Physionet Challenge 2013

Fetal electrocardiograms, direct and abdominal with reference heartbeat annotations

Monitoring fetal heart rate (FHR) variability plays a fundamental role in fetal state assessment. Reliable FHR signal can be obtained from an invasive direct fetal electrocardiogram (FECG), but this is limited to labour. Alternative abdominal (indirect) FECG signals can be recorded during pregnancy and labour. Quality, however, is much lower and the maternal heart and uterine contractions provide sources of interference. Here, we present ten twenty-minute pregnancy signals and 12 five-minute labour signals. Abdominal FECG and reference direct FECG were recorded simultaneously during labour. Reference pregnancy signal data came from an automated detector and were corrected by clinical experts. The resulting dataset exhibits a large variety of interferences and clinically significant FHR patterns. We thus provide the scientific community with access to bioelectrical fetal heart activity signals that may enable the development of new methods for FECG signals analysis, and may ultimately advance the use and accuracy of abdominal electrocardiography methods.Web of Science71art. no. 20

Fetal Electrocardiogram Processing Using Template Subtraction Methods

Cílem diplomové práce je zpracování plodového elektrokardiogramu za pomocí šablonového odčítání. Na začátku práce je probrána problematika vývoje kardiovaskulárního systému plodu a poté se práce věnuje rešerši na metody šablonového odčítání a jejich matematickému popisu. Praktická část je zaměřena na zpracování signálu využitím šablonových metod s následnou detekcí jednotlivých plodových QRS komplexů. Používané metody šablonového odčítání v diplomové práci jsou TS, TS – Cerutti, TS – Suzanna, TS – PCA a TS – LP. Extrahované signály fEKG jsou na konci vykreslovány v grafickém uživatelském rozhraní prostředí Matlab.The aim of the diploma thesis is to process fetal electrocardiogram using template subtraction. At the beginning of the thesis, the issue of the development of the fetal cardiovascular systém is discussed and then thesis is devoted to a review for template subtraction methods and their mathematical description. The practical part is focused on signal processing using template methods with subsequent detection of individual fetal QRS complexes. Evaluation of fetal ECG extraction is based on fetal heart rate. Method used in thesis are TS, TS – Cerutti, TS – Suzanna, TS – PCA and TS – LP. The extracted fECG signals are plotted in graphical user interface in Matlab environment.450 - Katedra kybernetiky a biomedicínského inženýrstvívýborn